1. Field of the Invention
The present invention relates to a radar image processing device and a radar image processing method which extracts a region of land cover change of an observation target from time series of image data obtained at different times by a radar device equipped in a flying object such as an artificial satellite and an airplane.
2. Description of the Related Art
Conventionally, techniques are put in practical use having a part of a ground surface as an observation target and which observes a change of the observation target. For example, there is known a method in which a change of a ground object is extracted using optical image data. However, because it is not possible to acquire optical image data at bad weather, there is a problem in that the method is not practical.
In consideration of this, a technique has been proposed for observing a change of a ground surface using a Synthetic Aperture Radar (SAR) or the like. The SAR is an active sensor which measures reflection, from the ground surface, of a microwave pulse irradiated from an artificial satellite or the like, and can observe in daytime and at nights and regardless of the weather. For example, Patent Document 1 discloses a technique which detects a change based on a correlation value of two radar image data of the observation target obtained at different times by a radar device. In addition, Non-Patent Document 1 discloses a technique which extracts a region of change of a ground surface based on a change in time of a backscattering coefficient of the radar image data.
[Patent Document 1] JP 2006-3302 A
[Non-Patent Document 1] Yuichiro USUDA, et al., “A study on Early Detection Method for Land Cover Change using Time-series SAR Images”, Journal of the Japan Society of Photogrammetry and Remote Sensing, 44, 6, 48-57, 2005
In the above-described Patent Document 1, a coherence value indicating a correlation of two radar images obtained at different times is calculated, and the change with respect to time of an observation target occurring between the different times when the two radar images are obtained is detected through a threshold value process based on the coherence value, taking advantage of the fact that the coherence value is 1 when the two radar images completely match each other and approaches 0 as the difference between the two radar images is increased. However, in a region of vegetation, the coherence value is reduced due to change in season. In addition, there has been a problem in that when the baseline length of the SAR is large, the coherence value is reduced over the entire image.
In Non-Patent Document 1, on the other hand, a backscattering coefficient which depends on the projections and depressions on the ground surface and dielectric constant obtained from the SAR is obtained, a difference of scattering coefficients between different times is calculated, and pixels having a difference of a predetermined threshold value or greater is extracted as a region of land cover change. However, there has been a problem in that the scattering coefficient may change due to a change in the amount of moisture in soil even though the surface is not changed and the scattering coefficient may significantly change for a building with a slight difference in the angle of incidence.
Because of these circumstances, it has been difficult to accurately extract the presence/absence of a change in a ground surface by only one of the coherence value and the scattering coefficient, due to a difference in the imaging time, weather, angle of incidence, and ground coverage of the observation target.
In addition, when SAR data of a high resolution is used for extracting a region of land cover change such as a ground coverage, if a small region of land cover change is to be extracted, an excessive extraction part becomes large. For example, there is a possibility that a moving object such as an automobile is excessively extracted.
Moreover, the mechanism of the scattering of the microwave by a ground object is very complex and a speckle noise in a shape of dispersed dots is present in the image. Because of this, when it is determined whether or not there is a change merely by the threshold value, there is a possibility that many noise is erroneously extracted.